CN114035437B - Anti-interference control method and device for outlet temperature of trough type solar thermal-arrest field - Google Patents
Anti-interference control method and device for outlet temperature of trough type solar thermal-arrest field Download PDFInfo
- Publication number
- CN114035437B CN114035437B CN202111414420.0A CN202111414420A CN114035437B CN 114035437 B CN114035437 B CN 114035437B CN 202111414420 A CN202111414420 A CN 202111414420A CN 114035437 B CN114035437 B CN 114035437B
- Authority
- CN
- China
- Prior art keywords
- model
- type solar
- solar thermal
- field
- control
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 71
- 230000000694 effects Effects 0.000 claims abstract description 10
- 230000008569 process Effects 0.000 claims description 27
- 238000010521 absorption reaction Methods 0.000 claims description 11
- 239000011521 glass Substances 0.000 claims description 11
- 230000002902 bimodal effect Effects 0.000 claims description 6
- 230000005855 radiation Effects 0.000 abstract description 7
- 230000001629 suppression Effects 0.000 abstract description 6
- 230000008859 change Effects 0.000 description 4
- 238000012546 transfer Methods 0.000 description 4
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000010438 heat treatment Methods 0.000 description 2
- 239000002184 metal Substances 0.000 description 2
- 238000010248 power generation Methods 0.000 description 2
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010612 desalination reaction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000005057 refrigeration Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000013535 sea water Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Feedback Control In General (AREA)
Abstract
The application provides an anti-interference control method and device for outlet temperature of a trough type solar thermal-arrest field, wherein the method mainly comprises the following steps: according to the trough type solar heat collection field, a linear discrete trough type solar heat collection field model is established; obtaining a generalized expansion state observation algorithm according to the linear discrete groove type solar thermal field model; and calculating an optimal control law according to the generalized expansion state observation algorithm. The application realizes unbiased control of the outlet temperature of the thermal-arrest field, introduces infinite time domain performance index into a predictive disturbance suppression control algorithm, ensures the stability of a closed loop system, and the obtained optimal model predictive control law is in the form of state feedback gain and can be directly integrated into an active disturbance rejection control framework, so that the predictive control has the capability of active disturbance suppression, thereby solving the problem that other disturbances except solar radiation cannot be evaluated in the prior art, and solving the problem that the delay effect of the feedback control law is overlarge.
Description
Technical Field
The application relates to the field of automatic control of thermal engineering, in particular to an anti-interference control method and device for outlet temperature of a trough type solar thermal collection field.
Background
The trough type heat collector is a heat collector which utilizes a photo-thermal conversion mode, realizes conversion from light energy to heat energy through focusing, reflection, absorption and other processes, and enables a heat exchange medium to reach a certain temperature so as to meet the requirements of different loads. The trough type heat collector belongs to the category of medium-high temperature heat collectors, can enable heat exchange working media to obtain higher temperature, and can be used in the life and production fields of thermal power generation, sea water desalination treatment, heating engineering, absorption refrigeration and the like. Because of the wide application prospect of solar energy, solar energy is the main energy source of the trough collector. Solar trough collectors dominate solar energy utilization systems, providing a source of heat for the system, and their efficiency and investment costs can impact the efficiency and economy of the overall collector system. The trough type solar heat collector adopts a vacuum glass tube structure, namely, an inner tube adopts a metal tube plated with a high-absorptivity selective absorption layer, a heating medium is moved in the tube, the glass tube is arranged at the outermost part, and vacuum is pumped between the glass tube and the metal tube so as to inhibit convection and conduction heat loss.
The outlet temperature of the trough type solar thermal-collecting field is directly related to the operation safety and economy of the whole solar generator set, the power generation efficiency is affected by the fact that the outlet temperature is too low, and the heat transfer of heat conduction oil in the pipe is deteriorated due to the fact that the outlet temperature is too high. The parameter is therefore one of the process parameters that need to be monitored with great importance during the operation of the unit. The control objective of the heat collection field is to keep the outlet temperature of the heat collection field near the rated value or track the change of the set value by controlling the flow rate of the heat conduction oil.
However, the thermal field exit temperature is one of the more difficult systems to control. The main reasons are two: firstly, the system has the characteristics of large delay, nonlinearity and strong coupling; second, there are many disturbances of the system, including external disturbances, i.e. solar radiation and inlet conduction oil temperature variations and internal disturbances, i.e. dynamic and parametric disturbances like time variations. Most of the above-mentioned disturbances are not measurable or difficult to measure accurately. The presence of these disturbances greatly increases the control difficulty. At present, a control scheme combining PID control, adaptive control, robust control and Kalman filter is generally adopted. In these control strategies, a kalman filter is used as a feed forward to observe the effects of external disturbances, which are then compensated for in a feedback controller. However, on the one hand, the kalman filter cannot take into account the estimation of other disturbances than solar radiation, and on the other hand, the aforementioned feedback control law cannot reduce the effect of the delay.
Disclosure of Invention
Aiming at the problem that other interferences of solar radiation cannot be evaluated in the prior art and the problem that the delay influence of a feedback control law is too large, the application provides the optimal prediction anti-interference control method for the outlet temperature of the trough type solar thermal-arrest field, which can further realize unbiased control of the outlet temperature of the solar thermal-arrest field under the condition that disturbance exists, thereby solving the defects in the prior art.
The application provides an anti-interference control method for outlet temperature of a trough type solar thermal-arrest field, which comprises the following steps:
s10, establishing a linear discrete groove type solar heat collection field model according to the groove type solar heat collection field;
s20, obtaining a generalized expansion state observation algorithm according to the linear discrete slot type solar thermal field model;
and S30, calculating an optimal control law according to the generalized expansion state observation algorithm.
Preferably, the establishing a linear discrete slot type solar thermal field model in S10 is as follows:
s11, linearizing a known nonlinear trough solar thermal-arrest field model by a first-order Taylor expansion method at a steady-state working condition:
wherein x= [ x ] 1 ,...,x n ,x n+1 ,...,x 2n ,x 2n+1 ,...,x 3n ] T =[t H (1),...,t H (n),t a (1),...,t a (n),t g (1),...,t g (n)] T N represents that the heat collecting tube is divided into n sections and t is divided into two sections according to the length H (j),t a (j),t g (j) Respectively representing the relative values of the temperatures of the outlet heat conduction oil, the absorption tube and the glass cover of the j-th section of the heat collecting tube; t is t H (j)=T H (j)-T H,out,r ,t a (j)=T a (j)-T a,r (j),t g (j)=T g (j)-T g,r (j),j=1,2...,n;y m Representing the relative value of the measurable output, i.e. y m =x; y represents a control output relative value, namely a relative value of the temperature of the heat conduction oil at the outlet of the heat collection field; u=q H -q H,r Is the relative value of the flow of the heat conduction oil, d i Represents the external disturbance, namely solar irradiance and the heat collection field inlet temperature; ΔA m And O (·) represent parameter perturbation and higher order minor terms, respectively; wherein the external disturbance, the parameter perturbation and the higher order small term are expressed as B as lumped disturbance dc d i ;
S12, discretizing the linearized model to obtain a linear discrete model:
in the method, in the process of the application,x k ,y mk and y k Respectively represent x, y m And discretized value of y, B d Is a parameter to be designed.
Preferably, in S20, a generalized extended state observation algorithm is obtained according to the linear discrete slot type solar thermal field model:
s21, representing the linear discrete model as an expanded form
In the method, in the process of the application,in an expanded state->
S22, designing corresponding generalized expansion state observation:
in the method, in the process of the application,and->Respectively is xi k And y mk L is the observed gain to be designed, which can be designed according to the pole configuration.
Preferably, in S30, according to the generalized extended state observation algorithm, an optimal control law is calculated as:
s31, at the moment k, lumped disturbance d is based on generalized expansion state observation algorithm k Observing to obtain its estimated value
S32, converting the effect of lumped interference into steady state estimation of state quantity and input quantity (x ss ,u ss ) In (a): from the following components
Is available in the form ofI.e.
S33, calculating a bimodal control law of a deviation form:
wherein, c k+i To control the degree of freedom, n c Is the length of the first modality;
s34, the control in the form of deviation is rhythmically substituted into a linear discretization model, and phi=a-BK is defined,is available in the form of
S35, defineAnd expansion variable->Calculating z k Dynamic characteristics of (3):
s36, deducing each variable of the deviation form:
wherein,
s37, establishing an optimal model to predict the anti-interference control problem:
the following infinite time domain performance indexes are adopted:
in the method, in the process of the application,q and R are weight matrixes;
substituting (9) and (10) into (11) to obtain the final optimal model predictive anti-interference control problem:
s.t. system (2)
S38, solving an optimal control law: by finding extreme value requirementsIs available in the form of
And (3) combining (4), (6), (7) and (13) to obtain the final control law:
in the method, in the process of the application,K t =(K o M 1 +M 3 )B d 。
preferably, the device comprises:
the solar heat collection field model is used for establishing a linear discrete groove type solar heat collection field model according to the groove type solar heat collection field;
the generalized extended state observation module is used for obtaining a generalized extended state observation algorithm according to the linear discrete slot type solar thermal-arrest field model;
and the optimal control law module calculates the optimal control law according to the generalized expansion state observation algorithm.
Preferably, the solar thermal-arrest field model is:
s11, linearizing a known nonlinear trough solar thermal-arrest field model by a first-order Taylor expansion method at a steady-state working condition:
wherein x= [ x ] 1 ,...,x n ,x n+1 ,...,x 2n ,x 2n+1 ,...,x 3n ] T =[t H (1),...,t H (n),t a (1),...,t a (n),t g (1),...,t g (n)] T N represents that the heat collecting tube is divided into n sections and t is divided into two sections according to the length H (j),t a (j),t g (j) Respectively representing the relative values of the temperatures of the outlet heat conduction oil, the absorption tube and the glass cover of the j-th section of the heat collecting tube; t is t H (j)=T H (j)-T H,out,r ,t a (j)=T a (j)-T a,r (j),t g (j)=T g (j)-T g,r (j),j=1,2...,n;y m Representing the relative value of the measurable output, i.e. y m =x; y represents a control output relative value, namely a relative value of the temperature of the heat conduction oil at the outlet of the heat collection field; u=q H -q H,r Is the relative value of the flow of the heat conduction oil, d i Represents the external disturbance, namely solar irradiance and the heat collection field inlet temperature; ΔA m And O (·) represent parameter perturbation and higher order minor terms, respectively; wherein the external disturbance, the parameter perturbation and the higher order small term are expressed as B as lumped disturbance dc d i ;
S12, discretizing the linearized model to obtain a linear discrete model:
in the method, in the process of the application,x k ,y mk and y k Respectively represent x, y m And discretized value of y, B d Is a parameter to be designed.
Preferably, the generalized extended state observation module is:
s21, representing the linear discrete model as an expanded form
In the method, in the process of the application,in an expanded state->
S22, designing corresponding generalized expansion state observation:
in the method, in the process of the application,and->Respectively is xi k And y mk L is the observed gain to be designed, which can be designed according to the pole configuration.
Preferably, the optimal control law module is:
s31, at the moment k, lumped disturbance d is based on generalized expansion state observation algorithm k Observing to obtain its estimated value
S32, converting the effect of lumped interference into steady state estimation of state quantity and input quantity (x ss ,u ss ) In (a): from the following components
Is available in the form ofI.e.
S33, calculating a bimodal control law of a deviation form:
wherein, c k+i To control the degree of freedom, n c Is the length of the first modality;
s34, the control in the form of deviation is rhythmically substituted into a linear discretization model, and phi=a-BK is defined,is available in the form of
S35, defineAnd expansion variable->Calculating z k Dynamic characteristics of (3):
s36, deducing each variable of the deviation form:
wherein,
s37, establishing an optimal model to predict the anti-interference control problem:
the following infinite time domain performance indexes are adopted:
in the method, in the process of the application,q and R are weight matrixes;
substituting (9) and (10) into (11) to obtain the final optimal model predictive anti-interference control problem:
s.t. system (2)
S38, solving an optimal control law: by finding extreme value requirementsIs available in the form of
And (3) combining (4), (6), (7) and (13) to obtain the final control law:
in the method, in the process of the application,K t =(K o M 1 +M 3 )B d 。
the application realizes unbiased control of the outlet temperature of the thermal-arrest field by establishing a generalized extended state observation algorithm, introduces an infinite time domain performance index into a predictive disturbance suppression control algorithm, ensures the stability of a closed loop system, and ensures that the obtained optimal model predictive control law is in a state feedback gain form and can be directly integrated into an active disturbance rejection control framework, so that predictive control has the capability of active disturbance suppression, thereby solving the problem that other disturbances except solar radiation cannot be evaluated in the prior art and simultaneously solving the problem that the delay of the feedback control law has overlarge influence.
Drawings
FIG. 1 is a flow chart of a method for controlling outlet temperature anti-interference of a trough type solar thermal field according to an embodiment;
FIG. 2 is a diagram showing an optimal predicted anti-interference control structure for outlet temperature of a trough type solar thermal-arrest field according to an embodiment;
FIG. 3 is a graph showing the temperature of the heat transfer oil at the inlet of the thermal field versus time in one embodiment;
FIG. 4 is a graph showing the flow rate of heat transfer oil in a thermal collection field versus time in an embodiment;
fig. 5 is a block diagram of a device for controlling outlet temperature anti-interference of a trough type solar thermal field in an embodiment.
Detailed Description
The application realizes unbiased control of the outlet temperature of the thermal-arrest field by establishing a generalized extended state observation algorithm, introduces an infinite time domain performance index into a predictive disturbance suppression control algorithm, ensures the stability of a closed loop system, and ensures that the obtained optimal model predictive control law is in a state feedback gain form and can be directly integrated into an active disturbance rejection control framework, thereby ensuring that predictive control has the capability of active disturbance suppression, solving the problem that other disturbances except solar radiation cannot be evaluated in the prior art and solving the problem that the delay of the feedback control law has overlarge influence.
Fig. 1 is a schematic flow chart of an anti-interference control method for outlet temperature of a trough type solar thermal-arrest field.
S10, establishing a linear discrete groove type solar heat collection field model according to the groove type solar heat collection field.
Specifically, the establishing a linear discrete slot type solar thermal-arrest field model in S10 is as follows:
s11, linearizing a known nonlinear trough solar thermal-arrest field model by a first-order Taylor expansion method at a steady-state working condition:
wherein x= [ x ] 1 ,...,x n ,x n+1 ,...,x 2n ,x 2n+1 ,...,x 3n ] T =[t H (1),...,t H (n),t a (1),...,t a (n),t g (1),...,t g (n)] T N represents that the heat collecting tube is divided into n sections and t is divided into two sections according to the length H (j),t a (j),t g (j) Respectively representing the relative values of the temperatures of the outlet heat conduction oil, the absorption tube and the glass cover of the j-th section of the heat collecting tube; t is t H (j)=T H (j)-T H,out,r ,t a (j)=T a (j)-T a,r (j),t g (j)=T g (j)-T g,r (j),j=1,2...,n;y m Representing the relative value of the measurable output, i.e. y m =x; y represents a control output relative value, namely a relative value of the temperature of the heat conduction oil at the outlet of the heat collection field; u=q H -q H,r Is the relative value of the flow of the heat conduction oil, d i Represents the external disturbance, namely solar irradiance and the heat collection field inlet temperature; ΔA m And O (·) represent parameter perturbation and higher order minor terms, respectively; wherein the external disturbance, the parameter perturbation and the higher order small term are expressed as B as lumped disturbance dc d i ;
S12, discretizing the linearized model to obtain a linear discrete model:
in the method, in the process of the application,x k ,y mk and y k Respectively represent x, y m And discretized value of y, B d Is a parameter to be designed.
S20, obtaining a generalized expansion state observation algorithm according to the linear discrete groove type solar thermal field model.
Specifically, the generalized extended state observation algorithm is obtained according to the linear discrete slot type solar thermal field model in S20:
s21, representing the linear discrete model as an expanded form
In the method, in the process of the application,in an expanded state->
S22, designing corresponding generalized expansion state observation:
in the method, in the process of the application,and->Respectively is xi k And y mk L is the observed gain to be designed, which can be designed according to the pole configuration.
And S30, calculating an optimal control law according to the generalized expansion state observation algorithm.
Specifically, in S30, according to the generalized extended state observation algorithm, an optimal control law is calculated as follows:
s31, at kCarved, lumped disturbance d based on generalized expansion state observation algorithm k Observing to obtain its estimated value
S32, converting the effect of lumped interference into steady state estimation of state quantity and input quantity (x ss ,u ss ) In (a): from the following components
Is available in the form ofI.e.
S33, calculating a bimodal control law of a deviation form:
wherein, c k+i To control the degree of freedom, n c Is the length of the first modality;
s34, the control in the form of deviation is rhythmically substituted into a linear discretization model, and phi=a-BK is defined,is available in the form of
S35, defineAnd expansion variable->Calculating z k Dynamic characteristics of (3):
s36, deducing each variable of the deviation form:
wherein,
s37, establishing an optimal model to predict the anti-interference control problem:
the following infinite time domain performance indexes are adopted:
in the method, in the process of the application,q and R are weight matrixes;
substituting (9) and (10) into (11) to obtain the final optimal model predictive anti-interference control problem:
s.t. system (2)
S38, solving an optimal control law: by finding extreme value requirementsIs available in the form of
And (3) combining (4), (6), (7) and (13) to obtain the final control law:
in the method, in the process of the application,K t =(K o M 1 +M 3 )B d 。
FIG. 2 is a graph showing the effect of controlling the outlet temperature of the thermal-arrest field.
One specific embodiment is that first, a linear-discrete model is obtained
For a nonlinear thermal-arrest field model (15):
wherein, subscripts H, a, g, i and o respectively represent heat conducting oil, an absorption tube, a glass cover, an inside tube and an outside tube; t (T) H (j),T a (j),T g (j) Respectively representing the temperatures of the conduction oil, the absorption tube and the glass tube at the outlet of the j-th section. T (T) H (0)=T in And T H (n)=T H,out Representing the inlet and outlet temperatures of the thermal-arrest field respectively; q H Is the heat conduction oil flow rate, ρ is the density, c is the specific heat capacity, A is the cross-sectional area of the heat conduction pipe, P is the pipe diameter, deltal is the length of each section of pipe, h is the convective heat transfer coefficient, DNI is the irradiance, eta opt For optical efficiency, w is aperture width, T sky Is sky temperature, T atm Is the ambient temperature, σ is the Boltzmann constant, ε a Epsilon for absorption of emissivity of the tube wall g The emissivity of the glass cover is given, and Q is radiant heat. The whole heat collecting field tube is divided into two sections, namely n=2, so that the outlet temperature T of the heat collecting field H,out =T H (2)。
T H,out,r (2) | q H,r (kg/s) | T a,r (2)(℃) | T g,r (2)(℃) | DNI r (W/m 2 ) | T H,in,r (℃) | T atm,r (℃) | T sky,r (℃) | |
#1 | 369.20 | 7 | 373.50 | 51.50 | 700 | 275 | 25 | 10 |
At the operating point #1 shown in the above table, the linearization object (15) can obtain a linear model shown in the formula (1) to obtain A m ,B m ,C m ,C o 。
Further, setting the sampling time to be 1 second, obtaining parameters A and B of the linear discrete model according to the formula (2), and designing B d =9×10 -3 I 6×6 。
And then obtaining a generalized extended state observation algorithm according to the linear discrete groove type solar thermal field model.
The object is restated to an expanded form as shown in equation (4), and the observer gain L is designed. Here, as can be seen from the rank criteria,it is considerable to configure the design L according to the principle that the pole amplitude is smaller than 1.
And finally, designing a compound optimal model predictive disturbance rejection controller.
At time k, disturbance d is based on generalized extended state observer (4) k Observing to obtain its estimated value
The effect of lumped interference is converted into steady state estimates of state and input quantities (x ss ,u ss ) In which, obtain-M 1 B d and-M 3 B d Is a value of (2).
Steady state estimation (x ss ,u ss ) Substituting the two-mode control law into the formula (7) to obtain the bimodal control law of the deviation form. At this time set up
K=[-0.1663,-0.1673,-0.0207,-0.0217,-0.0033,-0.0054],n c =4。
The control of the deviation form is rhythmically substituted into a linear discretization model (2) and Φ=a-BK is calculated to obtain a discrete form (8) of the closed loop system.
Calculating an expansion vector z according to (9) k Is described as a dynamic property ψ of a set of parameters.
The deviation form of each variable shown in the formula (10) is deduced.
Establishing an optimal model to predict the anti-interference control problem (12) at the momentS c =20.208I 4×4 ,S xc =0 6×4 Solving an optimal control law (14):
K o =[-0.1663,-0.1673,-0.0207,-0.0217,-0.0033,-0.0054]
K t =[0.0349-0.3337 0.0044-0.0404 0.0026 0.0035]
under the working condition, the added external interference is as follows: ramp interference with a slope of 18 ℃/h within 0.556-0.611 hours represents the temperature change of the heat conduction oil at the inlet of the heat collection field; after 1.25-1.667 hours, the amplitude is-20W/m 2 Representing a change in solar radiation, the result is shown in figure 3.
As can be seen from fig. 4, in the presence of the above-mentioned disturbances, the collector field outlet temperature T H,out Can still be quickly stabilized at 369.2 ℃ after smaller fluctuation, and the change amplitude of the heat conduction oil flow is smaller. The effectiveness of the research method in controlling the outlet temperature of the heat collection field is demonstrated.
In another aspect, referring to fig. 5, the present application provides a device for controlling outlet temperature anti-interference of a trough type solar thermal field, comprising:
the solar heat collection field model is used for establishing a linear discrete groove type solar heat collection field model according to the groove type solar heat collection field;
the generalized extended state observation module is used for obtaining a generalized extended state observation algorithm according to the linear discrete slot type solar thermal-arrest field model;
and the optimal control law module calculates the optimal control law according to the generalized expansion state observation algorithm.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the spirit of the application, which are within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (6)
1. An anti-interference control method for outlet temperature of a trough type solar thermal collection field is characterized by comprising the following steps:
s10, establishing a linear discrete groove type solar heat collection field model according to the groove type solar heat collection field;
s20, obtaining a generalized expansion state observation algorithm according to the linear discrete slot type solar thermal field model;
s30, calculating an optimal control law according to the generalized expansion state observation algorithm;
in S30, according to the generalized expansion state observation algorithm, an optimal control law is calculated as follows:
s31, at the moment k, lumped disturbance d is based on generalized expansion state observation algorithm k Observing to obtain its estimated value
S32, converting the effect of lumped interference into steady state estimation of state quantity and input quantity (x ss ,u ss ) In (a): from the following components
Is available in the form ofI.e.
S33, calculating a bimodal control law of a deviation form:
wherein, c k+i To control the degree of freedom, n c Is the length of the first modality;
s34, the control in the form of deviation is rhythmically substituted into a linear discretization model, and phi=a-BK is defined,is available in the form of
S35, defineAnd expansion variable->Calculating z k Dynamic characteristics of (3):
s36, deducing each variable of the deviation form:
wherein,
s37, establishing an optimal model to predict the anti-interference control problem:
the following infinite time domain performance indexes are adopted:
in the method, in the process of the application,wherein i=0,..infinity, Q and R are both weight matrices;
substituting (9) and (10) into (11) to obtain the final optimal model predictive anti-interference control problem:
s38, solving an optimal control law: by finding extreme value requirementsIs available in the form of
And (3) combining (4), (6), (7) and (13) to obtain the final control law:
in the method, in the process of the application,K t =(K o M 1 +M 3 )B d 。
2. the method for anti-interference control of outlet temperature of a trough type solar thermal-arrest field according to claim 1, wherein the establishing a linear discrete trough type solar thermal-arrest field model in S10 is as follows:
s11, linearizing a known nonlinear trough solar thermal-arrest field model by a first-order Taylor expansion method at a steady-state working condition:
wherein x= [ x ] 1 ,...,x n ,x n+1 ,...,x 2n ,x 2n+1 ,...,x 3n ] T =[t H (1),...,t H (n),t a (1),...,t a (n),t g (1),...,t g (n)] T N represents that the heat collecting tube is divided into n sections and t is divided into two sections according to the length H (j),t a (j),t g (j) Respectively representing the relative values of the temperatures of the outlet heat conduction oil, the absorption tube and the glass cover of the j-th section of the heat collecting tube; t is t H (j)=T H (j)-T H,out,r ,t a (j)=T a (j)-T a,r (j),t g (j)=T g (j)-T g,r (j),j=1,2...,n;y m Representing the relative value of the measurable output, i.e. y m =x; y represents a control output relative value, namely a relative value of the temperature of the heat conduction oil at the outlet of the heat collection field; u=q H -q H,r Is the relative value of the flow of the heat conduction oil, d i Represents the external disturbance, namely solar irradiance and the heat collection field inlet temperature; ΔA m And O (·) represent parameter perturbation and higher order minor terms, respectively; wherein the external disturbance, the parameter perturbation and the higher order small term are expressed as B as lumped disturbance dc d i ;
S12, discretizing the linearized model to obtain a linear discrete model:
in the method, in the process of the application,x k ,y mk and y k Respectively represent x, y m And discretized value of y, B d Is a parameter to be designed.
3. The method for controlling outlet temperature anti-interference of a trough type solar thermal-arrest field according to claim 1, wherein the generalized extended state observation algorithm is obtained according to the linear discrete trough type solar thermal-arrest field model in S20:
s21, representing the linear discrete model as an expanded form
In the method, in the process of the application,in an expanded state->
S22, designing corresponding generalized expansion state observation:
in the method, in the process of the application,and->Respectively is xi k And y mk L is the observed gain to be designed, which can be designed according to the pole configuration.
4. An anti-interference control device for outlet temperature of a trough type solar thermal-arrest field, which is applied to the anti-interference control method for outlet temperature of the trough type solar thermal-arrest field as claimed in any one of claims 1 to 3, and is characterized in that the device comprises:
the solar heat collection field model is used for establishing a linear discrete groove type solar heat collection field model according to the groove type solar heat collection field;
the generalized extended state observation module is used for obtaining a generalized extended state observation algorithm according to the linear discrete slot type solar thermal-arrest field model;
the optimal control law module calculates an optimal control law according to the generalized expansion state observation algorithm;
the optimal control law module is as follows:
s31, at the moment k, lumped disturbance d is based on generalized expansion state observation algorithm k Observing to obtain its estimated value
S32, converting the effect of lumped interference into steady state estimation of state quantity and input quantity (x ss ,u ss ) In (a): from the following components
Is available in the form ofI.e.
S33, calculating a bimodal control law of a deviation form:
wherein, c k+i To control the degree of freedom, n c Is the length of the first modality;
s34, the control in the form of deviation is rhythmically substituted into a linear discretization model, and phi=a-BK is defined,is available in the form of
S35, defineAnd expansion variable->Calculating z k Dynamic characteristics of (3):
s36, deducing each variable of the deviation form:
wherein,
s37, establishing an optimal model to predict the anti-interference control problem:
the following infinite time domain performance indexes are adopted:
in the method, in the process of the application,wherein i=0,..infinity, Q and R are both weight matrices;
substituting (9) and (10) into (11) to obtain the final optimal model predictive anti-interference control problem:
s38, solving an optimal control law: by finding extreme value requirementsIs available in the form of
And (3) combining (4), (6), (7) and (13) to obtain the final control law:
in the method, in the process of the application,K t =(K o M 1 +M 3 )B d 。
5. the anti-interference control device for outlet temperature of a trough type solar thermal-arrest field according to claim 4, wherein the solar thermal-arrest field model is as follows:
s11, linearizing a known nonlinear trough solar thermal-arrest field model by a first-order Taylor expansion method at a steady-state working condition:
wherein x= [ x ] 1 ,...,x n ,x n+1 ,...,x 2n ,x 2n+1 ,...,x 3n ] T =[t H (1),...,t H (n),t a (1),...,t a (n),t g (1),...,t g (n)] T N represents that the heat collecting tube is divided into n sections and t is divided into two sections according to the length H (j),t a (j),t g (j) Respectively representing the relative values of the temperatures of the outlet heat conduction oil, the absorption tube and the glass cover of the j-th section of the heat collecting tube; t is t H (j)=T H (j)-T H,out,r ,t a (j)=T a (j)-T a,r (j),t g (j)=T g (j)-T g,r (j),j=1,2...,n;y m Representing the relative value of the measurable output, i.e. y m =x; y represents a control output relative value, namely a relative value of the temperature of the heat conduction oil at the outlet of the heat collection field; u=q H -q H,r Is the relative value of the flow of the heat conduction oil, d i Represents the external disturbance, namely solar irradiance and the heat collection field inlet temperature; ΔA m And O (·) represent parameter perturbation and higher order minor terms, respectively; wherein the external disturbance, the parameter perturbation and the higher order small term are expressed as B as lumped disturbance dc d i ;
S12, discretizing the linearized model to obtain a linear discrete model:
in the method, in the process of the application,x k ,y mk and y k Respectively represent x, y m And discretized value of y, B d Is a parameter to be designed.
6. The anti-interference control device for outlet temperature of a trough type solar thermal field according to claim 4, wherein the generalized extended state observation module is:
s21, representing the linear discrete model as an expanded form
In the method, in the process of the application,in an expanded state->
S22, designing corresponding generalized expansion state observation:
in the method, in the process of the application,and->Respectively is xi k And y mk L is the observed gain to be designed, which can be designed according to the pole configuration.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111414420.0A CN114035437B (en) | 2021-11-25 | 2021-11-25 | Anti-interference control method and device for outlet temperature of trough type solar thermal-arrest field |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111414420.0A CN114035437B (en) | 2021-11-25 | 2021-11-25 | Anti-interference control method and device for outlet temperature of trough type solar thermal-arrest field |
Publications (2)
Publication Number | Publication Date |
---|---|
CN114035437A CN114035437A (en) | 2022-02-11 |
CN114035437B true CN114035437B (en) | 2023-11-21 |
Family
ID=80145526
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202111414420.0A Active CN114035437B (en) | 2021-11-25 | 2021-11-25 | Anti-interference control method and device for outlet temperature of trough type solar thermal-arrest field |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN114035437B (en) |
Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102425863A (en) * | 2011-09-19 | 2012-04-25 | 河海大学 | Method for controlling steam temperature of outlet of DSG (Direct Steam Generation) trough type solar thermal collector |
CN103390083A (en) * | 2013-07-23 | 2013-11-13 | 河海大学 | Method for simulating DSG (Direct Steam Generation) trough heat collector by using nonlinear distributed parameter model |
JP2015140937A (en) * | 2014-01-27 | 2015-08-03 | 株式会社日立製作所 | Solar thermal collection system and track correction method for same |
CN106766271A (en) * | 2016-12-15 | 2017-05-31 | 常州龙腾光热科技股份有限公司 | A kind of thermal-arrest field lens outlet temperature control method generated electricity for solar energy heating |
CN106769137A (en) * | 2016-12-09 | 2017-05-31 | 中国科学院电工研究所 | Paraboloid trough type solar heat-collector heat performance measuring apparatus and hot property Forecasting Methodology |
CN107577844A (en) * | 2017-08-04 | 2018-01-12 | 中国电力科学研究院 | The Forecasting Methodology and system of a kind of slot type photo-thermal power station mirror field outlet temperature |
CN108717306A (en) * | 2018-04-11 | 2018-10-30 | 河南城建学院 | A kind of DSG trough type solar heat-collectors vapor (steam) temperature Auto-disturbance-rejection Control |
CN109814385A (en) * | 2019-01-24 | 2019-05-28 | 国网天津市电力公司电力科学研究院 | It is a kind of based on the distributing of Active Disturbance Rejection Control with electric heating system and its method |
CN110286591A (en) * | 2019-06-21 | 2019-09-27 | 西安交通大学 | A kind of feed-forward and feedback composite control method and the investigating method based on this method |
CN110378076A (en) * | 2019-08-21 | 2019-10-25 | 南京工程学院 | A kind of groove type solar heat collecting field temperature deviation quantitative evaluating method |
CN209783010U (en) * | 2019-02-18 | 2019-12-13 | 源和电力股份有限公司 | Groove type solar parabolic reflector mechanism |
-
2021
- 2021-11-25 CN CN202111414420.0A patent/CN114035437B/en active Active
Patent Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102425863A (en) * | 2011-09-19 | 2012-04-25 | 河海大学 | Method for controlling steam temperature of outlet of DSG (Direct Steam Generation) trough type solar thermal collector |
CN103390083A (en) * | 2013-07-23 | 2013-11-13 | 河海大学 | Method for simulating DSG (Direct Steam Generation) trough heat collector by using nonlinear distributed parameter model |
JP2015140937A (en) * | 2014-01-27 | 2015-08-03 | 株式会社日立製作所 | Solar thermal collection system and track correction method for same |
CN106769137A (en) * | 2016-12-09 | 2017-05-31 | 中国科学院电工研究所 | Paraboloid trough type solar heat-collector heat performance measuring apparatus and hot property Forecasting Methodology |
CN106766271A (en) * | 2016-12-15 | 2017-05-31 | 常州龙腾光热科技股份有限公司 | A kind of thermal-arrest field lens outlet temperature control method generated electricity for solar energy heating |
CN107577844A (en) * | 2017-08-04 | 2018-01-12 | 中国电力科学研究院 | The Forecasting Methodology and system of a kind of slot type photo-thermal power station mirror field outlet temperature |
CN108717306A (en) * | 2018-04-11 | 2018-10-30 | 河南城建学院 | A kind of DSG trough type solar heat-collectors vapor (steam) temperature Auto-disturbance-rejection Control |
CN109814385A (en) * | 2019-01-24 | 2019-05-28 | 国网天津市电力公司电力科学研究院 | It is a kind of based on the distributing of Active Disturbance Rejection Control with electric heating system and its method |
CN209783010U (en) * | 2019-02-18 | 2019-12-13 | 源和电力股份有限公司 | Groove type solar parabolic reflector mechanism |
CN110286591A (en) * | 2019-06-21 | 2019-09-27 | 西安交通大学 | A kind of feed-forward and feedback composite control method and the investigating method based on this method |
CN110378076A (en) * | 2019-08-21 | 2019-10-25 | 南京工程学院 | A kind of groove type solar heat collecting field temperature deviation quantitative evaluating method |
Non-Patent Citations (3)
Title |
---|
Xianhua Gao.Active Disturbance Rejection Control for a Parabolic Trough Solar Field.《Proceedings of the 4th International Conference on Control and Computer Vision》.2021,第159-164页. * |
权学森.基于槽式太阳能辅助燃煤发电***的蓄热***设计.《太阳能学报》.2017,第38卷(第12期),第3216-3221页. * |
王万召.直接蒸汽发电槽式太阳能集热器蒸汽温度自抗扰控制.《热力发电》.2019,第48卷(第3期),第41-46页. * |
Also Published As
Publication number | Publication date |
---|---|
CN114035437A (en) | 2022-02-11 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Gálvez-Carrillo et al. | Nonlinear predictive control with dead-time compensator: Application to a solar power plant | |
Yilmaz et al. | Modeling of a mechanical cooling system with variable cooling capacity by using artificial neural network | |
Madani et al. | A descriptive and comparative analysis of three common control techniques for an on/off controlled Ground Source Heat Pump (GSHP) system | |
Cai et al. | Solar energy harvesting potential of a photovoltaic-thermoelectric cooling and power generation system: Bidirectional modeling and performance optimization | |
Dikmen et al. | Estimation and optimization of thermal performance of evacuated tube solar collector system | |
Sharma et al. | Optimization of a smooth flat plate solar air heater using stochastic iterative perturbation technique | |
Camacho et al. | Model predictive control in solar trough plants: A review | |
CN109240366A (en) | A kind of hot activation building system equivalent outdoor temperature forecast Control Algorithm | |
CN113159983B (en) | Coordinated control method for off-grid phosgene combined heat and power generation comprehensive energy system | |
CN112528542A (en) | Photo-thermal power generation system dynamic modeling method considering heat collector working mode and control method | |
CN114035437B (en) | Anti-interference control method and device for outlet temperature of trough type solar thermal-arrest field | |
Meligy et al. | Simulation and control of linear Fresnel reflector solar plant | |
Kandilli | A comparative study on the energetic-exergetic and economical performance of a photovoltaic thermal system (PVT) | |
Das et al. | Impacts of use PID control and artificial intelligence methods for solar air heater energy performance | |
Brus et al. | Black-box identification of solar collector dynamics with variant time delay | |
Zhuang et al. | A decentralized method for energy conservation of an HVAC system | |
Tianyi et al. | Experimental analysis of the thermal stability of the pressure control method for a variable flow air-conditioning water system | |
Fabri et al. | Modelling and temperature control of a wine fermentation process with solar cooling | |
Nelwan et al. | Steady state simulation on combination of glazed and unglazed flat plate solar collectors for air heating | |
Khademi et al. | Optimizing exergy efficiency of flat plate solar collectors using SQP and genetic algorithm | |
CN114815922B (en) | GPC and GPIO-based electric heating furnace temperature anti-interference control method | |
Ruelas et al. | Energy performance of a solar cavity receiver with neural output flow regulation under controlled conditions | |
Vasičkaninová et al. | Control of heat exchangers in series using neural network predictive controllers | |
Sbarbaro et al. | Dynamic output power optimization in hybrid PV/T panels | |
Sun et al. | Research on optimal control strategy of compound heating system based on model prediction |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |